Adv Biol Regul. 2025 Oct 30. pii: S2212-4926(25)00054-5. [Epub ahead of print] 101127
The unfolded protein response (UPR) is a central regulator of proteostasis, coordinating cellular adaptation to endoplasmic reticulum (ER) stress. It is comprised of three signaling branches: ATF6 (activating transcription factor 6), IRE1 (inositol-requiring enzyme 1), and PERK (protein kinase RNA-like ER kinase), which mediate transcriptional and translational reprogramming of the proteostasis network. These pathways display both functional redundancy and branch-specific activities. Dysregulated UPR signaling contributes to diverse pathologies: in cancer, UPR activation supports uncontrolled proliferation and treatment resistance, whereas in aging, proteostasis decline and diminished UPR responsiveness are hallmarks. Traditional approaches, including transcriptomics and western blotting, have been widely used to monitor UPR activity, but they offer limited insight into its regulation at the protein level. In contrast, liquid chromatography-tandem mass spectrometry (LC-MS/MS) based proteomics allows comprehensive, branch-specific profiling of UPR signaling. Recent advances, including data-independent acquisition (DIA) MS and automated sample preparation, have further improved sensitivity, reproducibility, and detection of low-abundance UPR target proteins. Proteomics thus provides a systematic and scalable framework to interrogate UPR regulation across cell types and disease models. When integrated with complementary datasets, protein-level measurements can uncover context-dependent molecular signatures of UPR activity, offering insights into disease mechanisms and guiding the rational design of targeted pharmacological interventions. Future work integrating high-resolution LC-MS/MS proteomics with tissue and single-cell analyses will further clarify the role of the UPR in health and disease.
Keywords: Activating transcription factor 6; Bottom-up proteomics; ER stress; Inositol requiring enzyme 1; Protein kinase R-like ER kinase; Proteomics automation; Proteostasis